MS Excel is a useful tool for genealogy because it assists in observing patterns that emerge out of data, especially when using it with the FAN (Friends Associates Neighbors) principle. Because were examining larger segments of a population whether it be neighborhoods or ethnic communities, genealogical sources provide invaluable demographic information that go beyond the traditional discipline of genealogy into social history. The trick to implementing this in spreadsheet software like Excel is easy, the hard part is sitting down to abstract records with this information, unless it happens to be the type of thing you enjoy.

Your data has the most meaning when you focus on a particular source to study. You can create some very convincing hypotheses with your data if you analyze the same population through separate studies that focus on one source and then draw comparisons when analyzing them as a whole. You can analyze a community through the federal census, WWI draft cards, naturalizations, draft registration, arrest records, and more.

You have the freedom to choose how many different types of facts you extract from the set of sources. It’s best to decide at the beginning, so your mind sticks with the routing you established at the start, rather then going back and extracting a new piece of data. It just feels like less work when you already doing something that could be considered tedious. However, the more parts of the record you analyze, the greater chance you can reveal some interesting observations about a particular population. How many of the people in the neighborhood were literate? How many families owned a radio? What types of occupations were performed in the neighborhood?

I picked a neighborhood of Eastern European immigrants from the 1920 Census to demonstrate this strategy. Of the 20 families I recorded, 70% of the individuals immigrated to the United States. As I extracted data from the census, there were several ways I could “sort” my data to present interesting observations:

1. To organize my list of names by a particular category, highlight the data with the “Select All” short key [for Macintosh and Windows, its Ctrl + A].

2. At the top bar of my menu, is a row of icons, including an icon with the letters Z, A, and a white arrow. This is the sort function and it may appear in another form, depending on what version you are working with.

3. Highlight the icon and it’s drop down menu, to see a list of options and levels for sorting. We want to use “Custom Sort.”

4. By clicking custom sort, a new window pops up with levels for sorting the data. You can select the column of data for which to sort by. I was curious to see a chronology of when people in this area arrived in the United States, so I’ll highlight the column for immigration year.

5. Then click on the icon that will arrange my data, either in an ascending (alphabetically or numerically) or descending fashion.

My interest led to this small section of the town’s population because of a work-related project and the fact that it was in the town in which I resided for 15 years. Near the Samson Cordage Works in Shirley, Massachusetts resided a majority of the town’s Polish and Russian population. As employees of the factory, they lived in company homes along Phoenix Street and Rodman Avenue in the Southeastern section of Shirley, close enough that they could walk home to lunch everyday. I can perform a custom sort again and this time sort by occupation. I can see more clearly the roles of different members in the neighborhood in regards to what they did for work. Each held a specific station at Samson Cordage Works, so it’s interesting to see where everyone was specifically positioned within the mill.

As I mentioned before, these techniques could be implemented with any set of data, regardless of size or content. Taking these easy steps to sort the data in different ways lends itself to conducting research that is more thorough and perhaps even breaking down genealogy brick walls.

For further reading, I suggest Colleen Fitzpatrick’s Forensic Genealogy who shows with many examples of how analyzing datasets in genealogy can lead to powerful research conclusions.